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Fable 5 – Median thinking declined in August

428 points · 293 comments · espeed

  1. mlmonkey · · focus · HN ↗
    Anecdotally, I have found the same. I spend a lot of time with these frontier models, brainstorming, etc. and the drop in performance from, say, week 1 to week 8 is often massive. Whereas in the beginning, it seemed like a capable research assistant, by the end of week 8 or so it starts acting like a puppy dog eager to make its 'master' happy for a few treats.
    1. physicallyIllfr · · focus · HN ↗
      Reminds me of how slot machine users swear the odds have changed on a machine.

      also when someone says you just have to prompt it a certain way it reminds me of people who think they can get better results out of a slot machine by pressing buttons in a certain order

      The providers of these models also design the UX similarly to slot machines (run it x amount of times for better results, multiplying your spend) this isnt a coincidence and they're playing into the gambler mentality, and probably hire UX designers that specialize in this.

      1. porridgeraisin · · focus · HN ↗
        Well, running an LLM X amount of times does give you better results provided you are willing to select the best one out of the X yourself.

        But I agree with your general point. One of the reasons subscription plans are cheaper because they modulate usage in this way based on demand. They can also recover compute more coarsely via usage resets (which give positive PR).

        1. zeroonetwothree · · focus · HN ↗
          At that point I might as well do it myself
          1. porridgeraisin · · focus · HN ↗
            Well yeah. If for some task you find it easier to just do it yourself then you should. But you can improve the situation even if you can't entirely automate it by automating parts of the verification thereby making it easier to human-do larger verifications when X>1. But in many cases even that is not possible.

            The progress however is such that the number of tasks that you can do with >p% automated and X=1 keeps increasing. So many times just waiting works. Of course, here also it changes from field to field. There are some tasks at which AI hasn't even gotten started, others where it has already peaked, others where it's increasing slowly, and others where it's increasing fast.

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